Dynamic Programming-Based Optimal Charging Scheduling for Electric Vehicles

Kuan Li, Ying Zhang, Chenglie Du, Tao You, Lu Bai, Jiaming Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The charging scheduling of electric vehicles not only affects the operation of the grid system, but also affects the charging cost of vehicle users. This paper studies the charging scheduling problem of electric vehicles from the user's perspective by considering the grid's as well as the user's needs. On the basis of real-time electricity prices, an electric vehicle charging scheduling system aiming at the lowest charging cost is designed and an optimal charging scheduling method based on dynamic programming is established. In order to reduce the unnecessary computational expenses, this paper optimizes the dynamic programming algorithm, and defines the state transition limit of the dynamic programming search space according to the actual constraints, which reduces the computational complexity. The simulation results show that, on the premise of satisfying the power constraints and user charging demands, the electric vehicles charging scheduling system can effectively reduce the charging cost and time. In addition, the charging process has little impact on the power system from the perspective of grid fluctuation.

Original languageEnglish
Title of host publication2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages545-550
Number of pages6
ISBN (Electronic)9781665460071
DOIs
StatePublished - 2022
Event7th IEEE International Conference on Intelligent Transportation Engineering, ICITE 2022 - Beijing, China
Duration: 11 Nov 202213 Nov 2022

Publication series

Name2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022

Conference

Conference7th IEEE International Conference on Intelligent Transportation Engineering, ICITE 2022
Country/TerritoryChina
CityBeijing
Period11/11/2213/11/22

Keywords

  • charging scheduling
  • dynamic programming
  • electric vehicles
  • real-time electricity price

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